code: def test_clean_cache(mocker):
      from llama_handler import LlamaHandler
  
      device = "cuda" if torch.cuda.is_available() else "cpu"
  
      handler = LlamaHandler()
  
      handler.context = mocker.MagicMock(name="context")
      handler.context.request_ids = {k: f"id{k+1}" for k in range(3)}
  
      handler.batch_idx_to_req_ids = [
          "id5",
          "id1",
          None,
          "id2",
          "id3",
          None,
          "id4",
          None,
      ]
      handler.max_bsz = len(handler.batch_idx_to_req_ids)
  
      handler.model = mocker.MagicMock(name="model")
      handler.model.layers = [mocker.MagicMock(name="layer")]
      handler.model.layers[0].attention.cache_k = -1 * torch.ones(
          (handler.max_bsz, 1), dtype=torch.long, device=device
      )
      handler.model.layers[0].attention.cache_k[0] = 5
      handler.model.layers[0].attention.cache_k[1] = 1
      handler.model.layers[0].attention.cache_k[3] = 2
      handler.model.layers[0].attention.cache_k[4] = 3
      handler.model.layers[0].attention.cache_k[6] = 4
  
      handler.model.layers[0].attention.cache_v = handler.model.layers[
          0
      ].attention.cache_k.clone()
  
      handler._clean_cache()
  
      assert handler.batch_idx_to_req_ids.index(None) == 3
      assert handler.batch_idx_to_req_ids[0] == "id3"
      assert handler.batch_idx_to_req_ids[1] == "id1"
      assert handler.batch_idx_to_req_ids[2] == "id2"
  
      assert handler.model.layers[0].attention.cache_k[0] == 3
      assert handler.model.layers[0].attention.cache_k[1] == 1
      assert handler.model.layers[0].attention.cache_k[2] == 2
  
      assert handler.model.layers[0].attention.cache_k.equal(
          handler.model.layers[0].attention.cache_v
      )
  
imports: import json
  import os
  import shutil
  import sys
  from collections import OrderedDict
  from multiprocessing import Process, Queue
  from pathlib import Path
  from unittest.mock import patch
  import pytest
  import requests
  import test_utils
  import torch
  import yaml
  from model_archiver.model_archiver_config import ModelArchiverConfig
  from ts.torch_handler.unit_tests.test_utils.mock_context import MockContext
label_desc: Use image node_id 6 for calling a global function with example usage: test_clean_cache(mocker) without return types